多局部节点异步航迹快速关联算法

doi:10.12305/j.issn.1001-506X.2023.03.07

摘要/Abstract

摘要：

为解决传统多维分配算法在多局部节点航迹关联中的运算量爆炸问题, 提出一种应用于多局部节点的异步航迹快速关联算法。首先, 引入虚拟航迹插值重构量测航迹, 然后定义虚实混合航迹序列的时序离散度(temporal discrete degree, TDD), 并在此基础上采用重新设计的多维次序匹配算法进行航迹关联判定, 待判定结束后进行TDD线性趋势系数(TDD-linear trend coefficient, TDD-LTC)检验, 以排除关联的多义性。仿真结果表明, 相同条件下, 所提算法在不损失正确关联率的同时, 可极大提升关联速度, 且在多局部节点、目标密集等情况下关联速度更具优势, 明显优于现有算法。

关键词: 航迹关联, 多局部节点, 虚实混合航迹序列, 时序离散度, 多维次序匹配

Abstract:

In order to solve the computational explosion of traditional multi-dimensional assignment algorithm in multi-local node track association, an asynchronous track fast association algorithm applied to multi-local node is proposed. Firstly, the virtual track interpolation is introduced to resconstruct the measured track. And then, the temporal discrete degree(TDD) of the virtual and real mixed track sequence is defined. On this basis, the redesigned multi-dimensional order matching algorithm is used to determine the track association. After the determination, the TDD-linear trend coefficient(TDD-LTC) test is carried out to eliminate the ambiguity of the association. Simulation results show that under the same conditions, the proposed algorithm can greatly improve the association speed without the loss of the association accuracy, and has more advantages in the case of multi-local node and dense targets, which is obviously superior to the existing algorithms.

Key words: track association, multi-local node, virtual and real mixed track sequence, temporal discrete degree(TDD), multi-dimensional order matching

中图分类号:

V271.4

国佳恩, 周正, 曾睿. 多局部节点异步航迹快速关联算法[J]. 系统工程与电子技术, 2023, 45(3): 669-677.

Jiaen GUO, Zheng ZHOU, Rui ZENG. Multi-local node asynchronous track fast correlation algorithm[J]. Systems Engineering and Electronics, 2023, 45(3): 669-677.

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目标	所属雷达	雷达采集的航迹数据	离散度	次序
1	1	(2.43, 3.16, 3.47, 4.73, 4.16, 4.87, 3.62, 5.17, 5.42)	0.004 8	2
	2	(3.49, 3.34, 3.34, 4.63, 4.38, 4.77, 5.27, 5.28, 4.93)	0.004 8	2
	3	(3.19, 2.59, 5.34, 4.02, 4.26, 5.60, 5.79, 5.68, 5.15)	0.004 8	2
2	1	(14.14, 14.29, 14.07, 15.09, 16.34, 17.35, 16.79, 16.77, 17.04)	0.005 4	1
	2	(15.34, 14.84, 15.28, 14.68, 16.56, 16.87, 17.21, 15.91, 17.19)	0.005 4	1
	3	(14.19, 14.86, 15.10, 16.35, 15.55, 15.99, 16.78, 16.46, 17.49)	0.005 4	1
3	1	(82.44, 83.10, 82.29, 82.81, 81.46, 81.81, 81.19, 81.18, 81.67)	0.004 3	3
	2	(81.91, 82.17, 82.30, 82.05, 81.00, 82.02, 81.72, 81.80, 81.15)	0.004 3	3
	3	(82.06, 81.68, 82.01, 82.91, 82.00, 82.12, 81.73, 80.73, 81.40)	0.004 3	3
虚拟航迹		(82.44, 83.10, 82.30, 82.91, 82.00, 82.12, 81.73, 81.80, 81.67)	-	-

节点	位置/km	采样周期/s	采样时延/s	测距误差/m	测角误差/(°)
1	(0, 0)	0.1	0	300	0.8
2	(0, 200)	0.2	0.5	150	0.8
3	(200, 0)	0.3	0.8	500	0.3
4	(200, 200)	0.3	0.3	200	0.8
5	(0, 100)	0.4	0	200	0.4
6	(200, 100)	0.4	0.4	500	0.7

节点数	本文算法	文献[5]算法	文献[13]算法
3	0.951 9	0.869 5	0.978 9
4	0.943 2	0.730 9	0.977 3
5	0.962 5	0.697 8	0.961 3
6	0.932 6	0.703 9	0.944 1

算法组合	①+③	①+④	②+③	②+④
运算量	2mnr	n^m·mr	2m²nr	n^m·m²r

算法组合	局部节点数
算法组合	3	4	5	6
①+③	0.022 1	0.029 3	0.035 6	0.041 7
①+④	0.165 9	0.257 5	0.347 7	0.458 5
②+③	0.084 8	0.114 1	0.136 8	0.167 8
②+④	3.225 1	4.887 5	6.361 8	8.141 8